A Review on Physiological Signals: Heart Rate Variability and Skin Conductance

2020 ◽  
pp. 387-399
Author(s):  
Ankita Soni ◽  
Kirti Rawal
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Skin Conductance ◽  
Physiological Signals

scholarly journals Stress Markers for Mental States and Biotypes of Depression and Anxiety: A Scoping Review and Preliminary Illustrative Analysis

2021 ◽  
Vol 5 ◽  
pp. 247054702110003
Author(s):  
Megan Chesnut ◽  
Sahar Harati ◽  
Pablo Paredes ◽  
Yasser Khan ◽  
Amir Foudeh ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Skin Conductance ◽  
Neural Circuit ◽  
Current Knowledge ◽  
Mental States ◽  
Classification Model ◽  
Depression And Anxiety ◽  
Stress Markers ◽  
Physiological Markers

Depression and anxiety disrupt daily function and their effects can be long-lasting and devastating, yet there are no established physiological indicators that can be used to predict onset, diagnose, or target treatments. In this review, we conceptualize depression and anxiety as maladaptive responses to repetitive stress. We provide an overview of the role of chronic stress in depression and anxiety and a review of current knowledge on objective stress indicators of depression and anxiety. We focused on cortisol, heart rate variability and skin conductance that have been well studied in depression and anxiety and implicated in clinical emotional states. A targeted PubMed search was undertaken prioritizing meta-analyses that have linked depression and anxiety to cortisol, heart rate variability and skin conductance. Consistent findings include reduced heart rate variability across depression and anxiety, reduced tonic and phasic skin conductance in depression, and elevated cortisol at different times of day and across the day in depression. We then provide a brief overview of neural circuit disruptions that characterize particular types of depression and anxiety. We also include an illustrative analysis using predictive models to determine how stress markers contribute to specific subgroups of symptoms and how neural circuits add meaningfully to this prediction. For this, we implemented a tree-based multi-class classification model with physiological markers of heart rate variability as predictors and four symptom subtypes, including normative mood, as target variables. We achieved 40% accuracy on the validation set. We then added the neural circuit measures into our predictor set to identify the combination of neural circuit dysfunctions and physiological markers that accurately predict each symptom subtype. Achieving 54% accuracy suggested a strong relationship between those neural-physiological predictors and the mental states that characterize each subtype. Further work to elucidate the complex relationships between physiological markers, neural circuit dysfunction and resulting symptoms would advance our understanding of the pathophysiological pathways underlying depression and anxiety.

Human Psychophysiology and PTSD

2016 ◽  
Author(s):  
Tanja Jovanovic ◽  
Seth Davin Norrholm
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Clinical Research ◽  
Fear Conditioning ◽  
Skin Conductance ◽  
Symptom Severity ◽  
Muscle Contractions ◽  
Pavlovian Fear Conditioning ◽  
Psychophysiological Measures ◽  
Biological Assessments

Psychophysiological measures provide useful tools for investigating neurobiological mechanisms of trauma-related sequalae. In addition, they can serve as objective biological assessments of symptom severity in clinical research. This chapter describes the methods for collection of psychophysiological measures. These include muscle contractions (startle), electrodermal skin conductance, heart rate, and heart rate variability (HRV) at baseline, under stress, and following Pavlovian fear conditioning. These approaches are important both for understanding biology as well as for providing objective biomarkers that can be compared translationally from animals to humans. It also reviews the literature that has used these measures in PTSD. The evidence to date strongly suggests that these data provide robust correlates of PTSD severity.

Effects of Electrical Acupuncture on Acupoint BL15 Evaluated in Terms of Heart Rate Variability, Pulse Rate Variability and Skin Conductance Response

2006 ◽  
Vol 34 (01) ◽  
pp. 23-36 ◽  
Author(s):  
Chih-Chieh Hsu ◽  
Ching-Sung Weng ◽  
Te-Sheng Liu ◽  
Yuh-Show Tsai ◽  
Yung-Hsien Chang
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Skin Conductance ◽  
Pulse Rate ◽  
Skin Conductance Response ◽  
Control Group ◽  
Pulse Rate Variability ◽  
Electrical Acupuncture ◽  
Experimental Group ◽  
Frequency Power

In this research, heart rate variability (HRV), pulse rate variability (PRV) and human skin conductance (SC) of all acupoints on Heart Meridian were used to evaluate the effects of electrical acupuncture (EA) on acupoint BL15 (Bladder Meridian). Ten healthy volunteers (aged 23 ± 6) were selected as the control group on the first day, and then used again as the experimental group on the second day. The control group received sham EA during the study, while subjects of the experimental group were stimulated by 2 Hz EA on acupoint BL15 for 10 minutes. Electrocardiogram (ECG), wrist blood pressure pulse meter and skin conductance response (SCR) device were used to measure and analyze HRV, PRV and SCR for the two groups before and after stimulation. From the spectrum analysis of ECG and pulse pressure graph, we found that the EA applied on BL15 could induce a significant increase in the normalized high frequency power (nHFP) component of HRV and PRV, as well as a significant decrease in the normalized low frequency power (nLFP) part ( p < 0.05). Moreover, both the heart rate and pulse rate were reduced in the analysis of the time domain of ECG and PRV. Furthermore, most of the SCR values at acupoints were decreased after stimulation. These results also indicate that the stimulation of BL15 by EA could cause relaxation, calmness and reduce feeling of tension or distress.

scholarly journals The Digi-NewB project for preterm infant sepsis risk and maturity analysis

2018 ◽  
Vol 10 (2-3) ◽  
Author(s):  
Alpo Värri ◽  
Antti Kallonen ◽  
Elina Helander ◽  
Andres Ledesma ◽  
Patrick Pladys
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Preterm Infant ◽  
Careful Analysis ◽  
Physiological Signals ◽  
P Value ◽  
Term Infants ◽  
Ecg Signals ◽  
Clinical Observations ◽  
Sepsis Risk

It is known from the literature that the careful analysis of the heart rate variability of a preterm infant can be used as a predictor of sepsis. The Digi-NewB project aims at collecting a database of at least 750 preterm infants including physiological signals, video and clinical observations. These data are used to design a decision support system for the early detection of sepsis and for the evaluation of the infant maturity. The preparation of the data for the exploratory analysis has turned out to be time-consuming. 190 infants have been recorded by March 2018 and of these, the R-R interval analysis of the ECG signals has been completed of 136 infants. The results of the project are still preliminary but seven heart rate variability parameters have been found to be different in preterm and full-term infants with a P value less than 0.01. The video analysis algorithm detecting the presence of personnel or relatives reached 96.8% of sensitivity and 95.1% of specificity.

scholarly journals Complexity-Based Decoding of the Coupling Among Heart Rate Variability (HRV) and Walking Path

2020 ◽  
Vol 11 ◽  
Author(s):  
Shahul Mujib Kamal ◽  
Mohammad Hossein Babini ◽  
Ondrej Krejcar ◽  
Hamidreza Namazi
Keyword(s):  
Heart Rate ◽  
Time Series ◽  
Heart Rate Variability ◽  
Fractal Dimension ◽  
Daily Life ◽  
Fractal Theory ◽  
Sample Entropy ◽  
Physiological Signals ◽  
Everyday Activity ◽  
First Time

Walking is an everyday activity in our daily life. Because walking affects heart rate variability, in this research, for the first time, we analyzed the coupling among the alterations of the complexity of walking paths and heart rate. We benefited from the fractal theory and sample entropy to evaluate the influence of the complexity of paths on the complexity of heart rate variability (HRV) during walking. We calculated the fractal exponent and sample entropy of the R-R time series for nine participants who walked on four paths with various complexities. The findings showed a strong coupling among the alterations of fractal dimension (an indicator of complexity) of HRV and the walking paths. Besides, the result of the analysis of sample entropy also verified the obtained results from the fractal analysis. In further studies, we can analyze the coupling among the alterations of the complexities of other physiological signals and walking paths.

EFFECT OF PHYSICAL ACTIVITIES ON HEART RATE VARIABILITY AND SKIN CONDUCTANCE

2021 ◽  
pp. 2150038
Author(s):  
Ankita Soni ◽  
Kirti Rawal
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Frequency Domain ◽  
Skin Conductance ◽  
Time Domain ◽  
Low Frequency ◽  
Physical Activities ◽  
Rr Intervals ◽  
Warm Up ◽  
Frequency Domain Methods

The sympathetic and parasympathetic function of the Autonomic Nervous System[Formula: see text]ANS[Formula: see text] is the primary cause of the variations in Heart Rate and Skin Conductance[Formula: see text]SC[Formula: see text] during different physical activities. This paper aims to analyze the effect of different physical activities i.e. (a) Supine (b) Standing and (c) Warm-up, on Heart Rate Variability (HRV) and SC. The standard dataset of 18 subjects has been used to analyze the effect of physical activities on the HRV and SC. In the used dataset, the subjects are in supine, standing, and warm-up positions. The linear methods (time domain & frequency domain) of HRV are implemented on the standard dataset for analyzing the effect of physical activities. It has been observed with the analysis of the HRV that the mean value of time domain methods i.e. the NN interval’s standard deviation (SDNN), the successive RR interval’s root mean square (RMSSD), RR intervals with more than 50 ms differences in between them (NN50), percentage of successive RR intervals that have the difference of more than 50 ms (pNN50) are decreased and the value of Heart rate (HR) increased when the activity has been changed from supine to standing and standing to the warm-up positions. The value of frequency domain methods, such as low frequency (LF) and the ratio of low and high frequency (LF/HF) increased, while the value of HF decreases as activity changes from supine to standing and from supine to warm-up position. Further, the increment is also observed in the value of SC when activity is switched from supine to standing and from standing to the warm-up position. It is concluded from the results that there is a significant decrement that is observed in the value of HRV, while the increment is observed in the value of SC and HR. Decrement of HRV reflects that the sympathetic activity is increased as activity changed from supine to standing and further from standing to warm-up positions.

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